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WTF
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29,63,35,37,26,51,35,58,30,61,45
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26,62,45,37,42,29,59,44,40
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35,63,62,18,56,65,42,77,82,63,76,50,47,69,57,65,85,70,38,67,89,74,71,67,70,71,95,77,45
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35
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63,61,45
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@ -1 +1,3 @@
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2022
2451
16
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2022
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2451
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16
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@ -67,7 +67,7 @@ def titanservice():
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file_list = glob.glob(source_dir + '/*.csv') #supposedly sorts by alphabetical order, skips reading teams.csv because of redundancy
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data = []
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files = [fn for fn in glob.glob('data/*.csv')
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if not (os.path.basename(fn).startswith('teams'))] #scores will be handled sperately
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if not (os.path.basename(fn).startswith('teams') or os.path.basename(fn).startswith('match') or os.path.basename(fn).startswith('notes') or os.path.basename(fn).startswith('observationType') or os.path.basename(fn).startswith('teamDBRef') )] #scores will be handled sperately
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for i in files:
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data.append(analysis.load_csv(i))
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@ -89,40 +89,40 @@ def titanservice():
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for i in range(len(measure)): #unpacks into specific teams
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ofbest_curve = [None]
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r2best_curve = [None]
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#ofbest_curve = [None]
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#r2best_curve = [None]
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line = measure[i]
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#print(line)
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x = list(range(len(line)))
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eqs, rmss, r2s, overfit = analysis.optimize_regression(x, line, 10, 1)
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#x = list(range(len(line)))
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#eqs, rmss, r2s, overfit = analysis.optimize_regression(x, line, 10, 1)
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beqs, brmss, br2s, boverfit = analysis.select_best_regression(eqs, rmss, r2s, overfit, "min_overfit")
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#beqs, brmss, br2s, boverfit = analysis.select_best_regression(eqs, rmss, r2s, overfit, "min_overfit")
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#print(eqs, rmss, r2s, overfit)
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ofbest_curve.append(beqs)
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ofbest_curve.append(brmss)
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ofbest_curve.append(br2s)
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ofbest_curve.append(boverfit)
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ofbest_curve.pop(0)
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#ofbest_curve.append(beqs)
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#ofbest_curve.append(brmss)
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#ofbest_curve.append(br2s)
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#ofbest_curve.append(boverfit)
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#ofbest_curve.pop(0)
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#print(ofbest_curve)
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beqs, brmss, br2s, boverfit = analysis.select_best_regression(eqs, rmss, r2s, overfit, "max_r2s")
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#beqs, brmss, br2s, boverfit = analysis.select_best_regression(eqs, rmss, r2s, overfit, "max_r2s")
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r2best_curve.append(beqs)
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r2best_curve.append(brmss)
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r2best_curve.append(br2s)
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r2best_curve.append(boverfit)
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r2best_curve.pop(0)
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#r2best_curve.append(beqs)
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#r2best_curve.append(brmss)
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#r2best_curve.append(br2s)
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#r2best_curve.append(boverfit)
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#r2best_curve.pop(0)
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#print(r2best_curve)
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measure_stats.append(teams[i] + list(analysis.basic_stats(line, 0, 0)) + list(analysis.histo_analysis(line, 1, -3, 3)) + ofbest_curve + r2best_curve)
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measure_stats.append(teams[i] + list(analysis.basic_stats(line, 0, 0)) + list(analysis.histo_analysis(line, 1, -3, 3)))
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stats.append(list(measure_stats))
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nishant = []
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@ -209,6 +209,15 @@ def pulldata():
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team_scores = []
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request_data_object = tba.req_team_matches(teams[i][0], 2019, "UDvKmPjPRfwwUdDX1JxbmkyecYBJhCtXeyVk9vmO2i7K0Zn4wqQPMfzuEINXJ7e5")
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json_data = request_data_object.json()
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#print(json_data)
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for i in range(len(json_data) - 1, -1, -1):
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if json_data[i].get('winning_alliance') == None or json_data[i].get('winning_alliance') == [] or json_data[i].get('winning_alliance') == "":
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print(json_data[i])
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json_data.remove(json_data[i])
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#print(json_data)
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json_data = sorted(json_data, key=lambda k: k.get('actual_time', 0), reverse=False)
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for j in range(len(json_data)):
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if "frc" + teams[i][0] in json_data[j].get('alliances').get('blue').get('team_keys'):
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@ -217,11 +226,11 @@ def pulldata():
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team_scores.append(json_data[j].get('alliances').get('red').get('score'))
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scores.append(team_scores)
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print(scores)
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with open("data/scores.csv", "w+", newline = '') as file:
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writer = csv.writer(file, delimiter = ',')
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writer.writerows(scores)
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def service():
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@ -231,17 +240,17 @@ def service():
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start = time.time()
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print("[OK]" + "time is: " + time.time())
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#print("[OK]" + "time is: " + time.time())
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print("[OK] starting calculations")
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fucked = False
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for i in range(0, 5):
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try:
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#try:
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titanservice()
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break
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except:
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#except:
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if (i != 4):
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print("[WARNING] failed, trying " + str(5 - i - 1) + " more times")
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else:
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